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Principal Component Analysis of HPLC Retention Data and Molecular Modeling Structural Parameters of Cardiovascular System Drugs in View of Their Pharmacological Activity

机译:鉴于其药理活性,心血管系统药物的HPLC保留数据主成分分析和分子建模结构参数

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Evaluation of relationships between molecular modeling structural parameters and high-performance liquid chromatography (HPLC) retention data of 11 cardiovascular system drugs by principal component analysis (PCA) in relation to their pharmacological activity was performed. The six retention data parameters were determined on three different HPLC columns (Nucleosil C18 AB with octadecylsilica stationary phase, IAM PC C10/C3 with chemically bounded phosphatidylcholine, and Nucleosil 100-5 OH with chemically bounded propanodiole), and using isocratically acetonitrile: Britton-Robinson buffer as the mobile phase. Additionally, molecular modeling studies were performed with the use of HyperChem software and MM+ molecular mechanics with the semi-empirical AM1 method deriving 20 structural descriptors. Factor analysis obtained with the use of various sets of parameters: structural parameters, HPLC retention data, and all 26 considered parameters, led to the extraction of two main factors. The first principal component (factor 1) accounted for 44–57% of the variance in the data. The second principal component (factor 2) explained 29–33% of data variance. Moreover, the total data variance explained by the first two factors was at the level of 73–90%. More importantly, the PCA analysis of the HPLC retention data and structural parameters allows the segregation of circulatory system drugs according to their pharmacological (cardiovascular) properties as shown by the distribution of the individual drugs on the plane determined by the two principal components (factors 1 and 2).
机译:通过主成分分析(PCA)评估了11种心血管系统药物的分子建模结构参数与高效液相色谱(HPLC)保留数据之间的关系,并对其药理活性进行了评估。在三个不同的HPLC色谱柱(具有十八烷基硅胶固定相的Nucleosil C18 AB,具有化学键合的磷脂酰胆碱的IAM PC C10 / C3和具有化学键合的丙二醇的Nucleosil 100-5 OH)上确定了六个保留数据参数,并使用了等度乙腈:Britton-鲁滨逊缓冲液作为流动相。此外,使用HyperChem软件和MM +分子力学以及半经验AM1方法进行分子建模研究,得出20个结构描述符。使用各种参数集进行的因子分析:结构参数,HPLC保留数据和所有26个考虑的参数,导致提取了两个主要因子。第一个主成分(因子1)占数据差异的44–57%。第二个主要成分(因子2)解释了数据差异的29-33%。此外,前两个因素解释的总数据差异在73-90%的水平。更重要的是,通过HPLC保留数据和结构参数的PCA分析,可以根据循环系统药物的药理(心血管)特性对循环系统药物进行分离,如通过两种主要成分确定的单个药物在平面上的分布(因子1)所示和2)。

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